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A multi-sensor optical relative navigation system for small satellite servicing

Giuseppe Napolano, Claudio Vela, Alessia Nocerino, Roberto Opromolla, Michele Grassi

2023Acta Astronautica34 citationsDOIOpen Access PDF

Abstract

This paper presents an innovative multi-sensor relative navigation module conceived to enable close-proximity operations for on-orbit servicing of small satellites. The module is composed of a Near-Infrared Laser Range Finder, acting both as range measurer and illuminator, and a monocular camera able to detect a set of reflecting fiducial markers installed on the target for pose estimation. Sensor fusion is performed in several points of the proposed processing pipeline, first following a cross-cueing logic in which the range aids the pose determination process, and later through the integration of both measurements into a Multiplicative Extended Kalman Filter for relative state estimation. The entire relative navigation architecture is first tested by numerically reproducing a close-range rendezvous trajectory of a chaser spacecraft moving toward the target, and using the open-source software Blender for synthetic image generation. Simulations are aimed at determining nominal relative state estimation accuracy (also considering variable sensors' acquisition rates) as well as performance under non-nominal conditions (e.g., due to a temporary loss of measurements). Focusing on the image processing and pose estimation pipeline, an in-depth analysis of the computational efficiency is then carried out by running the proposed algorithms on an embedded processing unit (i.e., the Raspberry Pi 4 Model B) using both synthetic data and real images collected within a dedicated experimental testbed. Numerical and experimental results demonstrate capability to attain pose and relative state estimates in line with accuracy requirements to ensure autonomous and safe close-proximity operations, e.g., up to sub-cm and sub-degree error levels in relative position and attitude respectively. In addition, the algorithm's computational runtime has shown to be compatible with real-time implementation at an acquisition frequency of 2 Hz.

Topics & Concepts

PoseComputer scienceComputer visionMonocular visionExtended Kalman filterReal-time computingArtificial intelligenceRange (aeronautics)Pipeline (software)Approximation errorKalman filterEngineeringAlgorithmProgramming languageAerospace engineeringSpace Satellite Systems and ControlRobotics and Sensor-Based LocalizationInertial Sensor and Navigation
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